Piezoelectric unimorph valve assembled on an LTCC substrate

In this paper a piezoelectric initially open valve was designed in low temperature co-fired ceramic (LTCC), manufactured using standard processes, and tested with integrated gas channels inside the LTCC module. Actuation of the valve was based on a piezoelectric unimorph with a diameter of 15 mm and thickness of 0.35 mm glued onto the fired LTCC substrate. Subsequently, a series of tests, including flow, displacement and switching time measurements, was carried out. Measurements of the valve revealed a flow of 143 ml/min under 1 bar pressure, leakage levels of 4%, valve displacement of 1.3 μm, and closing times less than 30 ms. Additional miniaturization and integration of an embedded valve in the LTCC will be pursued, enabling improved manufacturing as a batch process and micro- and nano-litre fluid management for various applications.     

Effect of micro-channel geometry on fluid flow and mixing

Understanding the flow fields at the micro-scale is key to developing methods of successfully mixing fluids for micro-scale applications. This paper investigates flow characteristics and mixing efficiency of three different geometries in micro-channels. The geometries of these channels were rectangular with a dimension of; 300 μm wide, 100 μm deep and 50 mm long. In first channel there was no obstacle and in the second channel there were rectangular blocks of dimension 300 μm long and 150 μm wide are placed in the flow fields with every 300 μm distance attaching along the channel wall. In the third geometry, there were 100 μm wide fins with 150° angle which were placed at a distance of 500 μm apart from each other attached with the wall along the 50 mm channel. Fluent software of Computational Fluid Dynamics (CFD) was used to investigate the flow characteristics within these microfluidic model for three different geometries. A species 2D model was created for three geometries and simulations were run in order to investigate the mixing behaviour of two different fluid with viscosity of water (1 mPa s). Models were only built to investigate the effect of geometry, therefore only one fluid with similar viscosity was used in these models. Velocity vector plots were used in the CFD analysis to visualise the fluid flow path. Mass fractions of fluid were used to analyse the mixing efficiency. Two different colours for water were used to simulate the effect of two different fluids. The results showed that the mixing behaviour strongly depended on the channel geometry when other parameters such as fluid inlet velocity, viscosity and pressure of fluids were kept constant. In two geometries lateral pressure and swirling vortexes were developed which provided better mixing results. Creation of swirling vortexes increased diffusion gradients which enhanced diffusive mixing.     

Empirical modeling of splitting tensile strength from cylinder compressive strength of concrete by genetic programming

Compressive strength and splitting tensile strength are both mechanical properties of concrete that are utilized in structural design. This study presents gene expression programming (GEP) as a new tool for the formulations of splitting tensile strength from compressive strength of concrete. For purpose of building the GEP-based formulations, 536 experimental data have been gathered from existing literature. The GEP-based formulations are developed for splitting tensile strength of concrete as a function of age of specimen and cylinder compressive strength. In experimental parts of this study, cylindrical specimens of 150 × 300 mm and 100 × 200 mm in dimensions are utilized. Training and testing sets of the GEP-based formulations are randomly separated from the complete experimental data. The GEP-based formulations are also validated with additional 173 data of experimental results other than the data used in training and testing sets of the GEP-based formulations. All of the results obtained from the GEP-based formulations are compared with the results obtained from experimental data, the developed regression-based formulation and formulas given by some national building codes. These comparisons showed that the GEP-based formulations appeared to well agree with the experimental data and found to be quite reliable.     

A miniature bio-inspired optic flow sensor based on low temperature co-fired ceramics (LTCC) technology

Low temperature co-fired ceramics (LTCC) technology is classically used in the field of radio frequencies to make items such as miniature transceivers for handheld devices. Here we harness the LTCC technology to autonomous micro-aerial vehicles (MAVs), a field in which small size and low mass are at a premium. Designing autonomous MAVs will be a highly challenging issue during the next few decades. Bio-inspired optic flow sensors, also known as elementary motion detector (EMD) circuits, have proved to be efficient means of providing animals and robots with visual guidance ability. The LTCC technology gives a good trade-off between the need for reliable optic flow sensors and the need for small-sized multiple electronic components. Comparisons with other technologies (PCB, analogue VLSI) show that LTCC technology is one of the most reliable solutions to the problem of obtaining reliable electronic EMDs that are small enough (area 7 mm × 7 mm) and light enough (mass 0.2 g) to be accommodated on-board a MAV. The output from our LTCC based optic flow sensors is largely invariant with respect to both contrast and spatial frequency.     

Optimization of the implant diameter and length in type B/2 bone for improved biomechanical properties: A three-dimensional finite element analysis

In this paper, effects of the implant diameter and length on the maximum equivalent stresses were evaluated in jaw bones, and maximum displacements examined in an implant–abutment complex by a finite element method. The implant diameter ranged from 3.0 mm to 5.0 mm, and implant length ranged from 6.0 mm to 16.0 mm. Results suggested that under axial load, the maximum equivalent stresses in cortical and cancellous bones decreased by 77.4% and 68.4% with the increasing of diameter and length respectively. Under buccolingual load, those decreased by 64.9% and 82.8%, respectively. The maximum displacements of implant-abutment complex decreased by 56.9% and 78.2% under axial and buccolingual load respectively. When the diameter exceeded 3.9 mm and the length exceeded 9.5 mm, the minimum stress/displacement was obtained. The evaluating targets were more sensitive to the diameter change than that of the length. Data indicated that the implant diameter affected stress distribution in jaw bone more than length did; and an implant diameter exceeding 3.9 mm and implant length exceeding 9.5 mm was the optimal selection for type B/2 bone in a cylinder implant by biomechanical considerations.     

Petri net based decision system modeling in real-time scheduling and control of flexible automotive manufacturing systems

This paper presents the design and the implementation of a Petri net (PN) model for the control of a flexible manufacturing system (FMS). A flexible automotive manufacturing system used in this environment enables quick cell configuration, and the efficient operation of cells. In this paper, we attempt to propose a flexible automotive manufacturing approach for modeling and analysis of shop floor scheduling problem of FMSs using high-level PNs. Since PNs have emerged as the principal performance modeling tools for FMS, this paper provides an object-oriented Petri nets (OOPNs) approach to performance modeling and to implement efficient production control. In this study, we modeled the system as a timed marked graph (TMG), a well-known subclass of PNs, and we showed that the problem of performance evaluation can be reduced to a simple linear programming (LP) problem with m − n + 1 variables and n constraints, where m and n represent the number of places and transitions in the marked graph, respectively. The presented PN based method is illustrated by modeling a real-time scheduling and control for flexible automotive manufacturing system (FAMS) in Valeo Turkey.     

Laser beam welded structures for a regional aircraft: weight,cost and carbon footprint savings

Laser beam welded structures offer great opportunities for the lightweight design of fuselage structures in order to reduce structural weight for increased fuel efficiency. Our main objective is to validate and demonstrate that laser beam welding (LBW) technology provides the best opportunities in terms of weight reduction, production time and energy consumption for manufacturing aircraft components. To this end, a comparison in terms of energy, process time, cost and carbon footprint is assessed against the ‘conventional’ manufacturing process of riveting, to prove that LBW is actually an environmental friendly process. Manufacturing of a four-stringer stiffened flat subscale component was the case of the present work that was called in the Clean Sky Eco-Design Airframe (EDA) project as the B1 demonstrator (742 mm × 384 mm). The LBW process has been broken down into several sub-processes and activities according to the Activity Based Costing (ABC) methodology and the weight reduction, production time and energy consumption results were compared against the respective of the riveting process. It was proved that for the specific subscale LBW component, it consumes half the energy and can be processed in less than half the time needed (in serial processing of the component) with riveting. Manufacturing of the component with the LBW process (door to door approach) is more environmentally friendly, since it produces 53% less CO_2e emissions than the respective riveted process. This is a clear advantage to this manufacturing process in order to assure a sustainable life cycle of the final product.     

A new flextensional piezoelectric ultrasonic motor—Design,fabrication and characterisation

This paper presents the techniques used for the characterisation of a new type of standing-wave piezoelectric ultrasonic motor. The motor uses a metallic flextensional amplifier, or “cymbal”, to convert the radial mode vibrations of a piezoelectric ceramic disc into flexural oscillations, which are further converted to produce rotary actuation by means of an elastic fin friction drive. The motor operates on a single-phase electrical supply. A beryllium copper rotor design with three-fin configuration was adopted. The best stall torque, no load speed, transient time and efficiency for a 25 mm motor were 2 N mm, 680 rpm, 2 ms and 4.8%, respectively. The operational characteristics of the motor were evaluated by using two methods: one based on the pulley–brake principle and one on high-speed imaging. The results obtained from using these two techniques are contrasted and compared.     

Precipitation forecasting by using wavelet-support vector machine conjunction model

A new wavelet-support vector machine conjunction model for daily precipitation forecast is proposed in this study. The conjunction method combining two methods, discrete wavelet transform and support vector machine, is compared with the single support vector machine for one-day-ahead precipitation forecasting. Daily precipitation data from Izmir and Afyon stations in Turkey are used in the study. The root mean square errors (RMSE), mean absolute errors (MAE), and correlation coefficient (R) statistics are used for the comparing criteria. The comparison results indicate that the conjunction method could increase the forecast accuracy and perform better than the single support vector machine. For the Izmir and Afyon stations, it is found that the conjunction models with RMSE=46.5 mm, MAE=13.6 mm, R=0.782 and RMSE=21.4 mm, MAE=9.0 mm, R=0.815 in test period is superior in forecasting daily precipitations than the best accurate support vector regression models with RMSE=71.6 mm, MAE=19.6 mm, R=0.276 and RMSE=38.7 mm, MAE=14.2 mm, R=0.103, respectively. The ANN method was also employed for the same data set and found that there is a slight difference between ANN and SVR methods.     

Predictive functional control of an axis positioning system with an estimator-based internal model

This paper deals with an application of the predictive functional control with a state estimator-based internal model (PFC_ EBIM). The PFC_ EBIM has been shown to be effective in simulation. However, neither detailed experimental validation nor comparison with other controllers has been reported thus far. Here, the PFC_ EBIM is implemented in a single-axis positioning system, and a few experimental tests are conducted. Tracking performance of the PFC_ EBIM, standard PFC, and P – PI control for both smooth and non-smooth reference signals are compared. The experimental results prove the effectiveness of the PFC_ EBIM.     

Integrated chip-size antennas for wireless microsystems: Fabrication and design considerations

This paper reports on fabrication and design considerations of an integrated folded shorted-patch chip-size antenna for applications in short-range wireless microsystems and operating inside the 5–6 GHz ISM band. Antenna fabrication is based on wafer-level chip-scale packaging (WLCSP) techniques and consists of two adhesively bonded glass wafers with patterned metallization and through-wafer electrical interconnects. Via formation in glass substrates is identified as the key fabrication step. Various options for via formation are compared and from these, a 193 nm excimer laser ablation is selected for fabrication of the antenna demonstrator. The fabricated antenna has dimensions of 4 mm × 4 mm × 1 mm, measured operating frequency of 5.05 GHz with a bandwidth of ∼200 MHz at the return loss of −10 dB and a simulated radiation efficiency of 60% were achieved.     

Simulation and experiment research on vaporizing liquid micro-thruster

In the present work, a micro-thruster chip with dimension of 19.5 mm × 9.5 mm was fabricated with MEMS technologies for the experiment study of vaporizing liquid micro-thruster. In addition, a full 3D computational model was constructed to simulate the aft section of a vaporizing liquid micro-thruster for investigating flow characteristics. The results show that there were four distinct flow patterns observed in this study including snake flow, vapor-droplet flow, vapor-droplet-jet flow, and vapor flow. To prevent the failure of micro-thruster chip from generating of snake flow, the heating treatment of an empty micro-thruster chip at 300 °C for 2 h was the key factor. The generation of vapor flow preliminarily proved that the concept of vaporizing liquid micro-thruster chip was feasible. Furthermore, the numerical model in this study successfully provided the thrust estimation. The channel cross-section of 1 mm × 100 μm designed in this study was fit for developing a micro-thruster of O(mN) (ranging from 1 to 6 mN approximately). The numerical simulation could match better with the experiment results for the vapor flow cases if the flow oscillation was taken into consideration, and the heating channel of micro-thruster was lengthened to completely vaporize the liquid water.     

Bivariate quality control using two-stage intelligent monitoring scheme

In manufacturing industries, it is well known that process variation is a major source of poor quality products. As such, monitoring and diagnosis of variation is essential towards continuous quality improvement. This becomes more challenging when involving two correlated variables (bivariate), whereby selection of statistical process control (SPC) scheme becomes more critical. Nevertheless, the existing traditional SPC schemes for bivariate quality control (BQC) were mainly designed for rapid detection of unnatural variation with limited capability in avoiding false alarm, that is, imbalanced monitoring performance. Another issue is the difficulty in identifying the source of unnatural variation, that is, lack of diagnosis, especially when dealing with small shifts. In this research, a scheme to address balanced monitoring and accurate diagnosis was investigated. Design consideration involved extensive simulation experiments to select input representation based on raw data and statistical features, artificial neural network recognizer design based on synergistic model, and monitoring–diagnosis approach based on two-stage technique. The study focused on bivariate process for cross correlation function, ρ = 0.1–0.9 and mean shifts, μ = ±0.75–3.00 standard deviations. The proposed two-stage intelligent monitoring scheme (2S-IMS) gave superior performance, namely, average run length, ARL₁ = 3.18–16.75 (for out-of-control process), ARL₀ = 335.01–543.93 (for in-control process) and recognition accuracy, RA = 89.5–98.5%. This scheme was validated in manufacturing of audio video device component. This research has provided a new perspective in realizing balanced monitoring and accurate diagnosis in BQC.     

Wavelet based shock wave and muzzle blast classification for different supersonic projectiles

The article presents a pattern recognition approach to acoustic shock wave and muzzle blast detection. Gunshot signatures are divided into multiple classes, given by combination of 3 types of supersonic weapons of different caliber: 7.62 mm, 5.56 mm and 9 mm and 3 types of acoustic events: shock wave, muzzle blast and reflections. The classification is performed on wavelet compressed 100 μs time frames. The experiment shows that the choice of a fitting wavelet base is crucial for the quality of recognition.     

Electrical properties of nickel oxide thin films for flow sensor application

In this work, Ni oxide thin films, with thermal sensitivity superior to Pt and Ni thin films, were formed through annealing of Ni films deposited by a r.f. magnetron sputtering. The annealing was carried out in the temperature range of 300–500 °C under atmospheric conditions. Resistivity of the resulting Ni oxide films were in the range of 10.5 μΩ cm/°C to 2.84 × 10⁴ μΩ cm/°C, depending on the extent of Ni oxidation. The temperature coefficient of resistance (TCR) of the Ni oxide films also depended on the extent of Ni oxidation; the average TCR of Ni oxide resistors, measured between 0 and 150 °C, were 5630 ppm/°C for the 300 °C and 2188 ppm/°C for 500 °C films. Because of their high resistivity and very linear TCR, Ni oxide thin films are superior to pure Ni and Pt thin films for flow and temperature sensor applications.     

Prediction of flow pattern of gas–liquid flow through circular microchannel using probabilistic neural network

The present study attempts to develop a flow pattern indicator for gas–liquid flow in microchannel with the help of artificial neural network (ANN). Out of many neural networks present in literature, probabilistic neural network (PNN) has been chosen for the present study due to its speed in operation and accuracy in pattern recognition. The inbuilt code in MATLAB R2008a has been used to develop the PNN. During training, superficial velocity of gas and liquid phase, channel diameter, angle of inclination and fluid properties such as density, viscosity and surface tension have been considered as the governing parameters of the flow pattern. Data has been collected from the literature for air–water and nitrogen–water flow through different circular microchannel diameters (0.53, 0.25, 0.100 and 0.050 mm for nitrogen–water and 0.53, 0.22 mm for air–water). For the convenience of the study, the flow patterns available in literature have been classified into six categories namely; bubbly, slug, annular, churn, liquid ring and liquid lump flow. Single PNN model is unable to predict the flow pattern for the whole range (0.53 mm–0.050 mm) of microchannel diameter. That is why two separate PNN models has been developed to predict the flow patterns of gas–liquid flow through different channel diameter, one for diameter ranging from 0.53 mm to 0.22 mm and another for 0.100 mm–0.05 mm. The predicted map and their transition boundaries have been compared with the corresponding experimental data and have been found to be in good agreement. Whereas accuracy in prediction of transition boundary obtained from available analytical models used for conventional channel is less for all diameter of channel as compared to the present work. The percentage accuracy of PNN (～94% for 0.53 mm ID and ～73% for 0.100 mm ID channel) has also been found to be higher than the model based on Weber number (～86% for 0.53 mm ID and ～36% for 0.05 mm ID channel).     

Modified Köhler illumination for LED-based projection display

Common projection optics use Köhler illumination to achieve a required lighting. These systems always prevent the realization of a compact optical configuration along with a high lumen output. Based on conventional Köhler illumination, a modified Köhler illumination system for LED-based projection display is presented in this paper, which can significantly reduce the system volume while allowing for adequate and homogeneous illumination. Equipped with the proposed system, a pocket-sized CF-LCoS projector with a physical dimension of 27.4 mm × 19.4 mm × 9.6 mm is designed, simulated and analyzed. Compared to conventional approaches, this design could offer an average 43% volume reduction with acceptable tolerance. To the best of our knowledge, the screen uniformity of 90.2% and the light efficiency of 56.5% are competitive as compared with those of the currently commercialized pocket-sized CF-LCoS projectors.     

Taguchi-fuzzy multi output optimization (MOO) in high speed CNC turning of AISI P-20 tool steel

This paper presents the application of Taguchi method with logical fuzzy reasoning for multiple output optimization of high speed CNC turning of AISI P-20 tool steel using TiN coated tungsten carbide coatings. The machining parameters (cutting speed, feed rate, depth of cut, nose radius and cutting environment) are optimized with considerations of the multiple performance measures (surface roughness, tool life, cutting force and power consumption). Taguchi’s concepts of orthogonal arrays, signal to noise (S/N) ratio, ANOVA have been fuzzified to optimize the high speed CNC turning process parameters through a single comprehensive output measure (COM). The result analysis shows that cutting speed of 160 m/min, nose radius of 0.8 mm, feed of 0.1 mm/rev, depth of cut of 0.2 mm and the cryogenic environment are the most favorable cutting parameters for high speed CNC turning of AISI P-20 tool steel.     

Critical pressure for capillary valves in a Lab-on-a-Disk: CFD and flow visualization

Capillary valves are used as pressure barriers to control flow sequencing in microfluidic devices. Influence of valves height on liquid flow pattern and critical pressure are studied through flow visualization and CFD predictions (Gambit® 2.2.30 and FLUENT® 6.2.16). Both hydrophilic and hydrophobic walls are studied. Results show that the surface tension plays a major role in the liquid progress through the microchannel/valve and also in the valve filling process. Critical pressure varies linearly with the valve hydraulic diameter in the range 0.91 < D_h < 3.5 [mm] according to: P = 14.14 · D_h + 47.42 [Pa].     

A new statistical approach to automated quality control in manufacturing processes

Automated quality control is a key aspect of industrial maintenance. In manufacturing processes, this is often done by monitoring relevant system parameters to detect deviations from normal behavior. Previous approaches define “normalcy” as statistical distributions for a given system parameter, and detect deviations from normal by hypothesis testing. This paper develops an approach to manufacturing quality control using a newly introduced method: Bayesian Posteriors Updated Sequentially and Hierarchically (BPUSH). This approach outperforms previous methods, achieving reliable detection of faulty parts with low computational cost and low false alarm rates (∼0.1%). Finally, this paper shows that sample size requirements for BPUSH fall well below typical sizes for comparable quality control methods, achieving True Positive Rates (TPR) >99% using as few as n = 25 samples.